One of the major accomplishments in biology of the last century has been the sequencing of the human genome. This has brought about a revolution, allowing researchers to gain information on cellular proteins, function, and human health issues with entirely new tools. The principal reasons for the whirlwind of advances are the information-rich and broadly accessible genome- and protein-databases. However, in order to fully utilize these new scientific approaches, it remains imperative that the absolute quantitation range of the proteins, lipids, nucleic acids, and the many transient and quasi-stable species present in cells and tissues are determined. In addition, this information must be coupled to the dynamics of the reactions of all relevant species, especially the transient species of metabolism, e.g. reactive oxygen and nitrogen species. Therefore, we propose to address these critical issues in redox biology in this proposed research through four critical Specific Aims. In SA 1 and 2 we will experimentally determine these concentration ranges and needed kinetic and thermodynamic information and couple this with data in the literature. In SA 3 we will initiate the assembly of three categories of information in a publicly available set of databases. These will include: a) absolute concentrations (copy number) of all relevant species that define the redox environment of a cell/tissue -- this will include antioxidant enzymes and proteins, small molecule antioxidants or enzyme substrates, and ROS/RNS; b) the kinetic rate constants for the array of reactions for each species; and c) the thermodynamic parameters for all relevant redox couples. In the fourth SA we will develop initial deterministic or stochastic mathematical models that utilize these parameters to predict the biological state and biological functioning of cells and tissues. These models will be available as lumped-parameter (time-dependent only), 1-D or higher spatial dimension forms to reflect the complexity of the specific dynamic system at hand. Within the model, approximations of the confidence in the models predictability will be provided. These initial models, which will focus on species transport near the mitochondrion, will be publicly available for use in conjunction with the databases developed in SA 3. As experimental verification continues, both the databases and models can be expanded upon by the community to improve representation and prediction of how changes in the redox environment of cells and tissue change their basic biology. The information in these databases and the mathematical models will provide information that can guide the design of animal experiments, minimizing their use, and the development of clinical protocols to maximize success. [unreadable] [unreadable] UCR PORTION [unreadable] [unreadable] Dr. Victor G. Rodgers has moved to the University of California at Riverside. With modern systems of communication we have regular meetings to discuss our ongoing projects. With Skype we are able to conference very easily at no cost. He will on average devote 1.0 months/yr of his effort to the project. His efforts will be focused on Specific Aim 4, the development of modular mathematical algorithms to model the redoxome. He has extensive expertise in modeling kinetic and transport processes. He will also work with Professors Srinivason and Buettner to design the data bases so that there is a seamless interface with the mathematical modeling. He will also oversee a TBN graduate student at UCR that will be responsible for the day-to-day development of the modeling systems.Project Narrative: [unreadable] [unreadable] It is just now being realized that redox biochemistry is at the heart of the basic biology of the cell. In this work we propose to gather into publicly available databases thermodynamic, kinetic, and concentration information on the species at the heart of this redox biochemistry: antioxidants, reducing agents, antioxidant enzymes and proteins, as well as the transient and quasi-stable free radicals and related oxidants. We will construct and make available mathematical models to use this information to understand how the redox environment connects to cell biology and issues of human health; the models can guide experimental design to minimize the use of animals and maximize success in developing new treatments for human health problems. [unreadable] [unreadable] [unreadable] [unreadable]